Recently, onboard cameras have become common for the purpose of supporting safe driving of an automobile. For example, an onboard camera (image capture apparatus) is installed at a front or rear part of a vehicle to shoot a video image of surroundings of the vehicle. The shot video image is displayed on a display installed before a driver's seat. Thereby, a driver can confirm existence or nonexistence of an object, such as a pedestrian, existing around the vehicle when the vehicle is running.
Efforts are also being made for attracting a driver's attention not by simply displaying a video image of surroundings of a vehicle on a display but by detecting an object, such as a pedestrian, in advance by some means, and displaying a video image with detection result information added thereto or issuing a warning by voice.
As the means for detecting an object, such as a pedestrian, for example, such that is mounted with a sensor for sensing a heat source or distance, separately from an onboard camera has been the mainstream of the means. However, mounting of a separate sensor is disadvantageous from the viewpoint of cost and versatility, and it is desired that image recognizing means for detecting an object only by a video image of an onboard camera is put to practical use.
In the field of research, a method of using edge characteristics in a video image has been considered to be effective as a method for detecting an object by image recognition. A boosting method has been established in which a great number of video images of a detection target object is learned in advance and utilized as statistical data. In the field of research, an object detection method obtained by composing the method using edge characteristics and the boosting method has already reached to a practical level from the viewpoint of detection accuracy.
From the viewpoint of practical use, however, the above method for detecting an object by image recognition has a problem of processing time. In the case of image recognition, video image processing is complicated, and it is required to scan the whole video image. Therefore, it takes much time until an object detection result for one frame of video image is obtained. Therefore, there are a problem that the frame rate of object detection processing is lower than the frame rate of a camera, and a problem that delay time before obtaining an object detection result for a video image occurs.
To cope with such problems related to processing time, a technique of performing two-stage detection is disclosed according to an object detection device described in Patent Literature 1 in which a reduced image obtained by reducing an inputted image is created, existence or nonexistence of an object is roughly detected on the reduced image first, and then detection processing is performed again for the input image with the original size only when an object is detected on the reduced image. Thereby, scanning is performed substantially with the size of the reduced image, the detection processing can be sped up.
In the method described in Patent Literature 1, however, since detection processing is performed with the use of a reduced image, image characteristics used in object detection processing are lost by the reduction. Therefore, there is a problem that, especially when an image of an object detection target is originally captured in a small size on a video image, detection performance cannot be sufficiently obtained. As a factor of an image of an object detection target being captured in a small size, any one of a factor that a detection target object is originally small and a factor that a detection target object exists at a position at a long distance from a camera is conceivable, or both of the factors are conceivable. At this time, there are caused bad effects: in the former case, a bad effect that sufficient detection accuracy cannot be obtained depending on a detection target object, and, in the latter case, a bad effect that the range of the distance to a detectable object is shortened.